Rain removal for object tracking in image sequence

In this report, we will explore the various methods of rain detection with a number of real life motion images. With the use of Matlab’s Computer Vision Tool Box, algorithms are developed to apply different techniques of rain detection and subsequently rain removal on motion pictures. The ob...

Full description

Saved in:
Bibliographic Details
Main Author: Campbell, Calina Dionne Xiu Ping
Other Authors: Chau Lap Pui
Format: Final Year Project
Language:English
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/10356/54263
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-54263
record_format dspace
spelling sg-ntu-dr.10356-542632023-07-07T15:57:47Z Rain removal for object tracking in image sequence Campbell, Calina Dionne Xiu Ping Chau Lap Pui School of Electrical and Electronic Engineering DRNTU::Engineering In this report, we will explore the various methods of rain detection with a number of real life motion images. With the use of Matlab’s Computer Vision Tool Box, algorithms are developed to apply different techniques of rain detection and subsequently rain removal on motion pictures. The objective of the project is to come out with a program which can detect rain apart from various objects in the video. The detection must have minimal false positives and negatives. Subsequently, the detected rain particles will be removed from the video, hence leaving the viewers with a clearer and sharper image. The main software used in the project was Matlab’s Computer Vision. It was used to write out algorithms for the various methods of rain detection such as the chromatic constraint, dynamic model constraint, and k-means constraint. The program was successful in telling apart rain particles from other objects in the video and subsequently removing it. A combination of the chromatic constraint and k-means constraint algorithm was developed and it improved the detection of rain.   Bachelor of Engineering 2013-06-18T03:47:59Z 2013-06-18T03:47:59Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/54263 en Nanyang Technological University 58 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering
spellingShingle DRNTU::Engineering
Campbell, Calina Dionne Xiu Ping
Rain removal for object tracking in image sequence
description In this report, we will explore the various methods of rain detection with a number of real life motion images. With the use of Matlab’s Computer Vision Tool Box, algorithms are developed to apply different techniques of rain detection and subsequently rain removal on motion pictures. The objective of the project is to come out with a program which can detect rain apart from various objects in the video. The detection must have minimal false positives and negatives. Subsequently, the detected rain particles will be removed from the video, hence leaving the viewers with a clearer and sharper image. The main software used in the project was Matlab’s Computer Vision. It was used to write out algorithms for the various methods of rain detection such as the chromatic constraint, dynamic model constraint, and k-means constraint. The program was successful in telling apart rain particles from other objects in the video and subsequently removing it. A combination of the chromatic constraint and k-means constraint algorithm was developed and it improved the detection of rain.  
author2 Chau Lap Pui
author_facet Chau Lap Pui
Campbell, Calina Dionne Xiu Ping
format Final Year Project
author Campbell, Calina Dionne Xiu Ping
author_sort Campbell, Calina Dionne Xiu Ping
title Rain removal for object tracking in image sequence
title_short Rain removal for object tracking in image sequence
title_full Rain removal for object tracking in image sequence
title_fullStr Rain removal for object tracking in image sequence
title_full_unstemmed Rain removal for object tracking in image sequence
title_sort rain removal for object tracking in image sequence
publishDate 2013
url http://hdl.handle.net/10356/54263
_version_ 1772827098664140800